[GigaCourse.Com] Udemy - A Complete Guide on TensorFlow 2.0 using Keras API

Creation Time	Aug. 20, 2024, 3:17 p.m.
Last Access Time	Nov. 15, 2024, 10:17 a.m.
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Keywords	A on Complete Keras - Udemy 0 2 GigaCourse using TensorFlow Com Guide API
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Total Files	279
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01 - Introduction/001 Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit.mp4 146.3 MB
02 - TensorFlow 2.0 Basics/001 From TensorFlow 1.x to TensorFlow 2.0.mp4 114.8 MB
17 - Annex 3 - Recurrent Neural Networks Theory/005 LSTM Practical Intuition.mp4 107.5 MB
17 - Annex 3 - Recurrent Neural Networks Theory/004 LSTMs.mp4 88.9 MB
16 - Annex 2 - Convolutional Neural Networks Theory/005 Step 2 - Max Pooling.mp4 87.5 MB
17 - Annex 3 - Recurrent Neural Networks Theory/003 Vanishing Gradient.mp4 86.2 MB
16 - Annex 2 - Convolutional Neural Networks Theory/002 What are Convolutional Neural Networks.mp4 71.1 MB
16 - Annex 2 - Convolutional Neural Networks Theory/003 Step 1 - Convolution.mp4 65.6 MB
10 - Dataset Preprocessing with TensorFlow Transform (TFT)/005 Dataset preprocessing pipeline.mp4 59.8 MB
16 - Annex 2 - Convolutional Neural Networks Theory/007 Step 4 - Full Connection.mp4 58.6 MB
17 - Annex 3 - Recurrent Neural Networks Theory/002 What are Recurrent Neural Networks.mp4 57.5 MB
04 - Convolutional Neural Networks/002 Building the Convolutional Neural Network.mp4 56.6 MB
07 - Deep Reinforcement Learning Theory/009 Action Selection Policies.mp4 54.4 MB
16 - Annex 2 - Convolutional Neural Networks Theory/009 Softmax & Cross-Entropy.mp4 51.4 MB
07 - Deep Reinforcement Learning Theory/002 The Bellman Equation.mp4 48.2 MB
06 - Transfer Learning and Fine Tuning/001 What is Transfer Learning.mp4 46.5 MB
06 - Transfer Learning and Fine Tuning/002 Project Setup.mp4 44.5 MB
15 - Annex 1 - Artificial Neural Networks Theory/002 The Neuron.mp4 43.7 MB
15 - Annex 1 - Artificial Neural Networks Theory/005 How do Neural Networks Learn.mp4 43.3 MB
07 - Deep Reinforcement Learning Theory/003 Markov Decision Process (MDP).mp4 42.4 MB
07 - Deep Reinforcement Learning Theory/008 Experience Replay.mp4 38.2 MB
07 - Deep Reinforcement Learning Theory/005 Temporal Difference.mp4 36.6 MB
08 - Deep Reinforcement Learning for Stock Market trading/012 Training loop - Step 2.mp4 36.1 MB
15 - Annex 1 - Artificial Neural Networks Theory/004 How do Neural Networks Work.mp4 35.2 MB
07 - Deep Reinforcement Learning Theory/006 Deep Q-Learning Intuition - Step 1.mp4 34.5 MB
15 - Annex 1 - Artificial Neural Networks Theory/007 Stochastic Gradient Descent.mp4 31.4 MB
07 - Deep Reinforcement Learning Theory/004 Q-Learning Intuition.mp4 29.3 MB
05 - Recurrent Neural Networks/001 Project Setup & Data Preprocessing.mp4 28.9 MB
08 - Deep Reinforcement Learning for Stock Market trading/007 Dataset Loader function.mp4 26.5 MB
15 - Annex 1 - Artificial Neural Networks Theory/006 Gradient Descent.mp4 25.7 MB
07 - Deep Reinforcement Learning Theory/001 What is Reinforcement Learning.mp4 24.9 MB
08 - Deep Reinforcement Learning for Stock Market trading/006 AI Trader - Step 5.mp4 23.3 MB
02 - TensorFlow 2.0 Basics/002 Constants, Variables, Tensors.mp4 23.1 MB
03 - Artificial Neural Networks/003 Building the Artificial Neural Network.mp4 22.9 MB
03 - Artificial Neural Networks/001 Project Setup.mp4 22.3 MB
03 - Artificial Neural Networks/002 Data Preprocessing.mp4 21.1 MB
16 - Annex 2 - Convolutional Neural Networks Theory/004 Step 1 Bis - ReLU Layer.mp4 20.6 MB
12 - Image Classification API with TensorFlow Serving/003 Project setup.mp4 19.9 MB
04 - Convolutional Neural Networks/003 Training and Evaluating the Convolutional Neural Network.mp4 19.8 MB
13 - TensorFlow Lite Prepare a model for a mobile device/003 Dataset preprocessing.mp4 19.7 MB
12 - Image Classification API with TensorFlow Serving/007 Serving the TensorFlow 2.0 Model.mp4 19.6 MB
02 - TensorFlow 2.0 Basics/003 Operations with Tensors.mp4 19.5 MB
14 - Distributed Training with TensorFlow 2.0/007 Final evaluation - Speed test normal model vs distributed model.mp4 19.1 MB
15 - Annex 1 - Artificial Neural Networks Theory/008 Backpropagation.mp4 17.7 MB
05 - Recurrent Neural Networks/003 Training and Evaluating the Recurrent Neural Network.mp4 17.3 MB
15 - Annex 1 - Artificial Neural Networks Theory/003 The Activation Function.mp4 17.3 MB
03 - Artificial Neural Networks/004 Training the Artificial Neural Network.mp4 17.3 MB
04 - Convolutional Neural Networks/001 Project Setup & Data Preprocessing.mp4 17.2 MB
10 - Dataset Preprocessing with TensorFlow Transform (TFT)/002 Initial dataset preprocessing.mp4 16.4 MB
12 - Image Classification API with TensorFlow Serving/005 Defining, training and evaluating a model.mp4 16.3 MB
11 - Fashion API with Flask and TensorFlow 2.0/005 Creating classify function.mp4 16.0 MB
11 - Fashion API with Flask and TensorFlow 2.0/001 Project Setup.mp4 15.5 MB
06 - Transfer Learning and Fine Tuning/009 Image Data Generators.mp4 15.4 MB
05 - Recurrent Neural Networks/002 Building the Recurrent Neural Network.mp4 15.0 MB
02 - TensorFlow 2.0 Basics/004 Strings.mp4 14.8 MB
06 - Transfer Learning and Fine Tuning/003 Dataset preprocessing.mp4 14.8 MB
06 - Transfer Learning and Fine Tuning/004 Loading the MobileNet V2 model.mp4 14.8 MB
07 - Deep Reinforcement Learning Theory/007 Deep Q-Learning Intuition - Step 2.mp4 14.6 MB
08 - Deep Reinforcement Learning for Stock Market trading/008 State creator function.mp4 14.2 MB
08 - Deep Reinforcement Learning for Stock Market trading/011 Training loop - Step 1.mp4 11.7 MB
09 - Data Validation with TensorFlow Data Validation (TFDV)/002 Loading the pollution dataset.mp4 11.6 MB
11 - Fashion API with Flask and TensorFlow 2.0/007 Sending API requests over internet to the model.mp4 11.6 MB
08 - Deep Reinforcement Learning for Stock Market trading/002 AI Trader - Step 1.mp4 11.5 MB
12 - Image Classification API with TensorFlow Serving/004 Dataset preprocessing.mp4 11.5 MB
03 - Artificial Neural Networks/005 Evaluating the Artificial Neural Network.mp4 11.2 MB
12 - Image Classification API with TensorFlow Serving/009 Sending the first POST request to the model.mp4 11.2 MB
16 - Annex 2 - Convolutional Neural Networks Theory/008 Summary.mp4 10.8 MB
12 - Image Classification API with TensorFlow Serving/006 Saving the model for production.mp4 10.3 MB
12 - Image Classification API with TensorFlow Serving/001 What is the TensorFlow Serving.mp4 10.1 MB
14 - Distributed Training with TensorFlow 2.0/003 Dataset preprocessing.mp4 10.0 MB
06 - Transfer Learning and Fine Tuning/007 Defining the transfer learning model.mp4 10.0 MB
10 - Dataset Preprocessing with TensorFlow Transform (TFT)/003 Dataset metadata.mp4 9.9 MB
12 - Image Classification API with TensorFlow Serving/008 Creating a JSON object.mp4 9.8 MB
09 - Data Validation with TensorFlow Data Validation (TFDV)/003 Creating dataset Schema.mp4 9.6 MB
06 - Transfer Learning and Fine Tuning/012 Fine Tuning model definition.mp4 9.4 MB
09 - Data Validation with TensorFlow Data Validation (TFDV)/001 Project Setup.mp4 9.1 MB
09 - Data Validation with TensorFlow Data Validation (TFDV)/005 Anomaly detection with TensorFlow Data Validation.mp4 9.0 MB
08 - Deep Reinforcement Learning for Stock Market trading/001 Project Setup.mp4 9.0 MB
10 - Dataset Preprocessing with TensorFlow Transform (TFT)/004 Preprocessing function.mp4 8.9 MB
06 - Transfer Learning and Fine Tuning/006 Adding a custom head to the pre-trained model.mp4 8.9 MB
09 - Data Validation with TensorFlow Data Validation (TFDV)/006 Preparing Schema for production.mp4 8.5 MB
11 - Fashion API with Flask and TensorFlow 2.0/003 Loading a pre-trained model.mp4 8.4 MB
10 - Dataset Preprocessing with TensorFlow Transform (TFT)/001 Project Setup.mp4 8.2 MB
12 - Image Classification API with TensorFlow Serving/002 TensorFlow Serving architecture.mp4 7.7 MB
14 - Distributed Training with TensorFlow 2.0/002 Project Setup.mp4 7.6 MB
06 - Transfer Learning and Fine Tuning/010 Transfer Learning.mp4 7.6 MB
11 - Fashion API with Flask and TensorFlow 2.0/006 Starting the Flask application.mp4 7.5 MB
17 - Annex 3 - Recurrent Neural Networks Theory/006 LSTM Variations.mp4 7.0 MB
08 - Deep Reinforcement Learning for Stock Market trading/005 AI Trader - Step 4.mp4 6.8 MB
16 - Annex 2 - Convolutional Neural Networks Theory/001 Plan of Attack.mp4 6.2 MB
08 - Deep Reinforcement Learning for Stock Market trading/004 AI Trader - Step 3.mp4 6.2 MB
13 - TensorFlow Lite Prepare a model for a mobile device/004 Building a model.mp4 6.1 MB
14 - Distributed Training with TensorFlow 2.0/004 Defining a non-distributed model (normal CNN model).mp4 6.0 MB
13 - TensorFlow Lite Prepare a model for a mobile device/001 What is the TensorFlow Lite.mp4 5.9 MB
08 - Deep Reinforcement Learning for Stock Market trading/010 Defining the model.mp4 5.6 MB
13 - TensorFlow Lite Prepare a model for a mobile device/005 Training, evaluating the model.mp4 5.5 MB
14 - Distributed Training with TensorFlow 2.0/001 What is the Distributed Training.mp4 5.3 MB
14 - Distributed Training with TensorFlow 2.0/006 Defining a distributed model.mp4 5.0 MB
08 - Deep Reinforcement Learning for Stock Market trading/003 AI Trader - Step 2.mp4 5.0 MB
06 - Transfer Learning and Fine Tuning/008 Compiling the Transfer Learning model.mp4 4.9 MB
11 - Fashion API with Flask and TensorFlow 2.0/002 Importing project dependencies.mp4 4.8 MB
15 - Annex 1 - Artificial Neural Networks Theory/001 Plan of Attack.mp4 4.8 MB
11 - Fashion API with Flask and TensorFlow 2.0/004 Defining the Flask application.mp4 4.4 MB
06 - Transfer Learning and Fine Tuning/014 Fine Tuning.mp4 4.3 MB
17 - Annex 3 - Recurrent Neural Networks Theory/001 Plan of Attack.mp4 4.2 MB
12 - Image Classification API with TensorFlow Serving/010 Sending the POST request to a specific model.mp4 4.0 MB
09 - Data Validation with TensorFlow Data Validation (TFDV)/007 Saving the Schema.mp4 3.8 MB
13 - TensorFlow Lite Prepare a model for a mobile device/006 Saving the model.mp4 3.8 MB
13 - TensorFlow Lite Prepare a model for a mobile device/002 Project setup.mp4 3.7 MB
06 - Transfer Learning and Fine Tuning/011 Evaluating Transfer Learning results.mp4 3.6 MB
06 - Transfer Learning and Fine Tuning/015 Evaluating Fine Tuning results.mp4 3.6 MB
13 - TensorFlow Lite Prepare a model for a mobile device/009 Saving the converted model.mp4 3.5 MB
08 - Deep Reinforcement Learning for Stock Market trading/009 Loading the dataset.mp4 3.3 MB
14 - Distributed Training with TensorFlow 2.0/005 Setting up a distributed strategy.mp4 3.2 MB
16 - Annex 2 - Convolutional Neural Networks Theory/006 Step 3 - Flattening.mp4 3.1 MB
13 - TensorFlow Lite Prepare a model for a mobile device/007 TensorFlow Lite Converter.mp4 2.7 MB
06 - Transfer Learning and Fine Tuning/005 Freezing the pre-trained model.mp4 2.6 MB
06 - Transfer Learning and Fine Tuning/013 Compiling the Fine Tuning model.mp4 2.5 MB
13 - TensorFlow Lite Prepare a model for a mobile device/008 Converting the model to a TensorFlow Lite model.mp4 2.1 MB
09 - Data Validation with TensorFlow Data Validation (TFDV)/004 Computing test set statistics.mp4 1.1 MB
11 - Fashion API with Flask and TensorFlow 2.0/19265454-Flask-API.zip 372.4 KB
09 - Data Validation with TensorFlow Data Validation (TFDV)/18573084-pollution-small.csv 72.7 KB
10 - Dataset Preprocessing with TensorFlow Transform (TFT)/18573088-pollution-small.csv 72.7 KB
07 - Deep Reinforcement Learning Theory/002 The Bellman Equation_en.vtt 28.2 KB
16 - Annex 2 - Convolutional Neural Networks Theory/007 Step 4 - Full Connection_en.vtt 26.6 KB
07 - Deep Reinforcement Learning Theory/005 Temporal Difference_en.vtt 26.1 KB
17 - Annex 3 - Recurrent Neural Networks Theory/004 LSTMs_en.vtt 25.9 KB
07 - Deep Reinforcement Learning Theory/003 Markov Decision Process (MDP)_en.vtt 24.5 KB
01 - Introduction/001 Welcome to the TensorFlow 2.0 course! Discover its structure and the TF toolkit_en.vtt 24.2 KB
15 - Annex 1 - Artificial Neural Networks Theory/002 The Neuron_en.vtt 23.2 KB
16 - Annex 2 - Convolutional Neural Networks Theory/009 Softmax & Cross-Entropy_en.vtt 23.2 KB
07 - Deep Reinforcement Learning Theory/009 Action Selection Policies_en.vtt 22.8 KB
17 - Annex 3 - Recurrent Neural Networks Theory/002 What are Recurrent Neural Networks_en.vtt 22.0 KB
07 - Deep Reinforcement Learning Theory/008 Experience Replay_en.vtt 21.9 KB
16 - Annex 2 - Convolutional Neural Networks Theory/003 Step 1 - Convolution_en.vtt 21.8 KB
16 - Annex 2 - Convolutional Neural Networks Theory/002 What are Convolutional Neural Networks_en.vtt 20.5 KB
07 - Deep Reinforcement Learning Theory/006 Deep Q-Learning Intuition - Step 1_en.vtt 20.5 KB
07 - Deep Reinforcement Learning Theory/004 Q-Learning Intuition_en.vtt 20.3 KB
16 - Annex 2 - Convolutional Neural Networks Theory/005 Step 2 - Max Pooling_en.vtt 19.9 KB
17 - Annex 3 - Recurrent Neural Networks Theory/003 Vanishing Gradient_en.vtt 19.1 KB
17 - Annex 3 - Recurrent Neural Networks Theory/005 LSTM Practical Intuition_en.vtt 19.1 KB
04 - Convolutional Neural Networks/002 Building the Convolutional Neural Network_en.vtt 18.3 KB
15 - Annex 1 - Artificial Neural Networks Theory/004 How do Neural Networks Work_en.vtt 18.1 KB
15 - Annex 1 - Artificial Neural Networks Theory/005 How do Neural Networks Learn_en.vtt 17.3 KB
07 - Deep Reinforcement Learning Theory/001 What is Reinforcement Learning_en.vtt 16.9 KB
02 - TensorFlow 2.0 Basics/001 From TensorFlow 1.x to TensorFlow 2.0_en.vtt 15.5 KB
03 - Artificial Neural Networks/003 Building the Artificial Neural Network_en.vtt 13.5 KB
15 - Annex 1 - Artificial Neural Networks Theory/006 Gradient Descent_en.vtt 12.9 KB
02 - TensorFlow 2.0 Basics/002 Constants, Variables, Tensors_en.vtt 12.0 KB
15 - Annex 1 - Artificial Neural Networks Theory/007 Stochastic Gradient Descent_en.vtt 11.3 KB
15 - Annex 1 - Artificial Neural Networks Theory/003 The Activation Function_en.vtt 11.0 KB
04 - Convolutional Neural Networks/003 Training and Evaluating the Convolutional Neural Network_en.vtt 10.0 KB
04 - Convolutional Neural Networks/001 Project Setup & Data Preprocessing_en.vtt 10.0 KB
05 - Recurrent Neural Networks/003 Training and Evaluating the Recurrent Neural Network_en.vtt 9.6 KB
03 - Artificial Neural Networks/004 Training the Artificial Neural Network_en.vtt 9.6 KB
10 - Dataset Preprocessing with TensorFlow Transform (TFT)/005 Dataset preprocessing pipeline_en.vtt 9.4 KB
03 - Artificial Neural Networks/002 Data Preprocessing_en.vtt 9.3 KB
05 - Recurrent Neural Networks/001 Project Setup & Data Preprocessing_en.vtt 9.3 KB
07 - Deep Reinforcement Learning Theory/007 Deep Q-Learning Intuition - Step 2_en.vtt 9.0 KB
08 - Deep Reinforcement Learning for Stock Market trading/008 State creator function_en.vtt 8.7 KB
16 - Annex 2 - Convolutional Neural Networks Theory/004 Step 1 Bis - ReLU Layer_en.vtt 8.5 KB
08 - Deep Reinforcement Learning for Stock Market trading/012 Training loop - Step 2_en.vtt 8.5 KB
05 - Recurrent Neural Networks/002 Building the Recurrent Neural Network_en.vtt 8.4 KB
02 - TensorFlow 2.0 Basics/003 Operations with Tensors_en.vtt 8.3 KB
02 - TensorFlow 2.0 Basics/004 Strings_en.vtt 8.1 KB
03 - Artificial Neural Networks/001 Project Setup_en.vtt 8.0 KB
10 - Dataset Preprocessing with TensorFlow Transform (TFT)/002 Initial dataset preprocessing_en.vtt 7.3 KB
08 - Deep Reinforcement Learning for Stock Market trading/007 Dataset Loader function_en.vtt 7.3 KB
12 - Image Classification API with TensorFlow Serving/001 What is the TensorFlow Serving_en.vtt 7.1 KB
08 - Deep Reinforcement Learning for Stock Market trading/002 AI Trader - Step 1_en.vtt 6.9 KB
11 - Fashion API with Flask and TensorFlow 2.0/001 Project Setup_en.vtt 6.9 KB
15 - Annex 1 - Artificial Neural Networks Theory/008 Backpropagation_en.vtt 6.5 KB
08 - Deep Reinforcement Learning for Stock Market trading/011 Training loop - Step 1_en.vtt 6.3 KB
12 - Image Classification API with TensorFlow Serving/009 Sending the first POST request to the model_en.vtt 6.1 KB
03 - Artificial Neural Networks/005 Evaluating the Artificial Neural Network_en.vtt 6.1 KB
09 - Data Validation with TensorFlow Data Validation (TFDV)/003 Creating dataset Schema_en.vtt 6.0 KB
08 - Deep Reinforcement Learning for Stock Market trading/006 AI Trader - Step 5_en.vtt 5.8 KB
06 - Transfer Learning and Fine Tuning/003 Dataset preprocessing_en.vtt 5.7 KB
16 - Annex 2 - Convolutional Neural Networks Theory/008 Summary_en.vtt 5.6 KB
06 - Transfer Learning and Fine Tuning/009 Image Data Generators_en.vtt 5.6 KB
06 - Transfer Learning and Fine Tuning/001 What is Transfer Learning_en.vtt 5.5 KB
10 - Dataset Preprocessing with TensorFlow Transform (TFT)/004 Preprocessing function_en.vtt 5.3 KB
11 - Fashion API with Flask and TensorFlow 2.0/005 Creating classify function_en.vtt 5.1 KB
12 - Image Classification API with TensorFlow Serving/006 Saving the model for production_en.vtt 5.0 KB
14 - Distributed Training with TensorFlow 2.0/003 Dataset preprocessing_en.vtt 4.9 KB
16 - Annex 2 - Convolutional Neural Networks Theory/001 Plan of Attack_en.vtt 4.9 KB
09 - Data Validation with TensorFlow Data Validation (TFDV)/005 Anomaly detection with TensorFlow Data Validation_en.vtt 4.8 KB
09 - Data Validation with TensorFlow Data Validation (TFDV)/002 Loading the pollution dataset_en.vtt 4.7 KB
12 - Image Classification API with TensorFlow Serving/004 Dataset preprocessing_en.vtt 4.6 KB
17 - Annex 3 - Recurrent Neural Networks Theory/006 LSTM Variations_en.vtt 4.5 KB
13 - TensorFlow Lite Prepare a model for a mobile device/001 What is the TensorFlow Lite_en.vtt 4.5 KB
10 - Dataset Preprocessing with TensorFlow Transform (TFT)/003 Dataset metadata_en.vtt 4.3 KB
12 - Image Classification API with TensorFlow Serving/007 Serving the TensorFlow 2.0 Model_en.vtt 4.3 KB
12 - Image Classification API with TensorFlow Serving/002 TensorFlow Serving architecture_en.vtt 4.3 KB
12 - Image Classification API with TensorFlow Serving/003 Project setup_en.vtt 4.1 KB
06 - Transfer Learning and Fine Tuning/012 Fine Tuning model definition_en.vtt 4.1 KB
09 - Data Validation with TensorFlow Data Validation (TFDV)/001 Project Setup_en.vtt 4.1 KB
09 - Data Validation with TensorFlow Data Validation (TFDV)/006 Preparing Schema for production_en.vtt 4.0 KB
13 - TensorFlow Lite Prepare a model for a mobile device/003 Dataset preprocessing_en.vtt 4.0 KB
14 - Distributed Training with TensorFlow 2.0/001 What is the Distributed Training_en.vtt 4.0 KB
11 - Fashion API with Flask and TensorFlow 2.0/007 Sending API requests over internet to the model_en.vtt 4.0 KB
14 - Distributed Training with TensorFlow 2.0/007 Final evaluation - Speed test normal model vs distributed model_en.vtt 4.0 KB
06 - Transfer Learning and Fine Tuning/002 Project Setup_en.vtt 3.9 KB
06 - Transfer Learning and Fine Tuning/006 Adding a custom head to the pre-trained model_en.vtt 3.7 KB
15 - Annex 1 - Artificial Neural Networks Theory/001 Plan of Attack_en.vtt 3.6 KB
11 - Fashion API with Flask and TensorFlow 2.0/003 Loading a pre-trained model_en.vtt 3.5 KB
14 - Distributed Training with TensorFlow 2.0/004 Defining a non-distributed model (normal CNN model)_en.vtt 3.4 KB
06 - Transfer Learning and Fine Tuning/004 Loading the MobileNet V2 model_en.vtt 3.3 KB
12 - Image Classification API with TensorFlow Serving/005 Defining, training and evaluating a model_en.vtt 3.3 KB
08 - Deep Reinforcement Learning for Stock Market trading/005 AI Trader - Step 4_en.vtt 3.2 KB
17 - Annex 3 - Recurrent Neural Networks Theory/001 Plan of Attack_en.vtt 3.2 KB
06 - Transfer Learning and Fine Tuning/008 Compiling the Transfer Learning model_en.vtt 3.1 KB
12 - Image Classification API with TensorFlow Serving/008 Creating a JSON object_en.vtt 3.1 KB
13 - TensorFlow Lite Prepare a model for a mobile device/004 Building a model_en.vtt 3.1 KB
08 - Deep Reinforcement Learning for Stock Market trading/010 Defining the model_en.vtt 2.9 KB
06 - Transfer Learning and Fine Tuning/010 Transfer Learning_en.vtt 2.8 KB
08 - Deep Reinforcement Learning for Stock Market trading/004 AI Trader - Step 3_en.vtt 2.6 KB
08 - Deep Reinforcement Learning for Stock Market trading/001 Project Setup_en.vtt 2.6 KB
10 - Dataset Preprocessing with TensorFlow Transform (TFT)/001 Project Setup_en.vtt 2.5 KB
11 - Fashion API with Flask and TensorFlow 2.0/006 Starting the Flask application_en.vtt 2.4 KB
16 - Annex 2 - Convolutional Neural Networks Theory/006 Step 3 - Flattening_en.vtt 2.4 KB
08 - Deep Reinforcement Learning for Stock Market trading/003 AI Trader - Step 2_en.vtt 2.4 KB
06 - Transfer Learning and Fine Tuning/014 Fine Tuning_en.vtt 2.3 KB
13 - TensorFlow Lite Prepare a model for a mobile device/002 Project setup_en.vtt 2.3 KB
18 - Bonus Lectures/003 FREE LEARNING RESOURCES FOR YOU.html 2.3 KB
12 - Image Classification API with TensorFlow Serving/010 Sending the POST request to a specific model_en.vtt 2.3 KB
11 - Fashion API with Flask and TensorFlow 2.0/002 Importing project dependencies_en.vtt 2.2 KB
13 - TensorFlow Lite Prepare a model for a mobile device/005 Training, evaluating the model_en.vtt 2.2 KB
13 - TensorFlow Lite Prepare a model for a mobile device/010 What's next.html 2.2 KB
14 - Distributed Training with TensorFlow 2.0/006 Defining a distributed model_en.vtt 2.1 KB
06 - Transfer Learning and Fine Tuning/007 Defining the transfer learning model_en.vtt 2.1 KB
10 - Dataset Preprocessing with TensorFlow Transform (TFT)/006 What's next.html 2.1 KB
09 - Data Validation with TensorFlow Data Validation (TFDV)/008 What's next.html 2.0 KB
14 - Distributed Training with TensorFlow 2.0/005 Setting up a distributed strategy_en.vtt 1.9 KB
13 - TensorFlow Lite Prepare a model for a mobile device/006 Saving the model_en.vtt 1.9 KB
06 - Transfer Learning and Fine Tuning/015 Evaluating Fine Tuning results_en.vtt 1.8 KB
08 - Deep Reinforcement Learning for Stock Market trading/009 Loading the dataset_en.vtt 1.8 KB
13 - TensorFlow Lite Prepare a model for a mobile device/009 Saving the converted model_en.vtt 1.8 KB
14 - Distributed Training with TensorFlow 2.0/002 Project Setup_en.vtt 1.7 KB
13 - TensorFlow Lite Prepare a model for a mobile device/007 TensorFlow Lite Converter_en.vtt 1.7 KB
11 - Fashion API with Flask and TensorFlow 2.0/004 Defining the Flask application_en.vtt 1.6 KB
06 - Transfer Learning and Fine Tuning/011 Evaluating Transfer Learning results_en.vtt 1.6 KB
06 - Transfer Learning and Fine Tuning/005 Freezing the pre-trained model_en.vtt 1.6 KB
09 - Data Validation with TensorFlow Data Validation (TFDV)/007 Saving the Schema_en.vtt 1.6 KB
01 - Introduction/004 BONUS Learning Path.html 1.4 KB
13 - TensorFlow Lite Prepare a model for a mobile device/008 Converting the model to a TensorFlow Lite model_en.vtt 1.3 KB
06 - Transfer Learning and Fine Tuning/013 Compiling the Fine Tuning model_en.vtt 1.3 KB
18 - Bonus Lectures/002 YOUR SPECIAL BONUS.html 1.1 KB
09 - Data Validation with TensorFlow Data Validation (TFDV)/004 Computing test set statistics_en.vtt 739 bytes
18 - Bonus Lectures/001 SPECIAL COVID-19 BONUS.html 722 bytes
01 - Introduction/003 BONUS 10 advantages of TensorFlow.html 613 bytes
04 - Convolutional Neural Networks/005 HOMEWORK SOLUTION Convolutional Neural Networks.html 573 bytes
04 - Convolutional Neural Networks/004 HOMEWORK Convolutional Neural Networks.html 500 bytes
03 - Artificial Neural Networks/006 HOMEWORK Artificial Neural Networks.html 493 bytes
01 - Introduction/002 Course Curriculum & Colab Toolkit.html 464 bytes
03 - Artificial Neural Networks/007 HOMEWORK SOLUTION Artificial Neural Networks.html 421 bytes
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06 - Transfer Learning and Fine Tuning/external-assets-links.txt 125 bytes
02 - TensorFlow 2.0 Basics/external-assets-links.txt 124 bytes
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16 - Annex 2 - Convolutional Neural Networks Theory/[GigaCourse.Com].url 49 bytes
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